Machine Learning With Python Programming : 2023 A Beginners Guide Machine Learning With Python Programming : 2023 A Beginners Guide

Machine Learning With Python Programming : 2023 A Beginners Guide

    • ¥750
    • ¥750

発行者による作品情報

Are you ready to dive into the fascinating world of Machine Learning and Artificial Intelligence? Do you want to understand the technology that powers everything from personalized recommendations to self-driving cars? If so, "Machine Learning With Python Programming : 2023 A Beginners Guide" is the book you've been waiting for.

This comprehensive guide takes you on an exciting journey from the basics of Python programming to the depths of neural networks and deep learning. It demystifies the complex world of machine learning, making it accessible and understandable, regardless of your background.

James begins by discussing machine learning and what it can do; introducing key mathematical and computational topics in an approachable manner; and walking you through the first steps in building, training, and evaluating learning systems. Step by step, you'll fill out the components of a practical learning system, broaden your toolbox, and explore some of the field's most sophisticated and exciting techniques. Whether you're a student, analyst, scientist, or hobbyist, this guide's insights will be applicable to every learning system you ever build or use.
Understand machine learning algorithms, models, and core machine learning conceptsClassify examples with classifiers, and quantify examples with regressorsRealistically assess performance of machine learning systemsUse feature engineering to smooth rough data into useful formsChain multiple components into one system and tune its performanceApply machine learning techniques to images and textConnect the core concepts to neural networks and graphical modelsLeverage the Python scikit-learn library and other powerful toolsAnd much more!
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ジャンル
コンピュータ/インターネット
発売日
2023年
10月27日
言語
EN
英語
ページ数
181
ページ
発行者
ORCHID PUBLISHING
販売元
Draft2Digital, LLC
サイズ
5.7
MB
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